Bump version to 1.0.0 (#1841)

* Bump version to 1.0.0 * Bump version to 1.0.0
open-mmlab · Apr 6, 2023 · d7c59f3 · d7c59f3
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diff --git a/README.md b/README.md
@@ -62,18 +62,16 @@ English | [简体中文](README_zh-CN.md)
 
 ## Latest Updates
 
-**The default branch is now `main` and the code on the branch has been switched to v1.0.0. The old `main` branch (v0.6.3) code now exists on the `0.x` branch.** If you have been using the `main` branch and encounter upgrade issues, please read the [Migration Guide](https://mmocr.readthedocs.io/en/dev-1.x/migration/overview.html) and notes on [Branches](https://mmocr.readthedocs.io/en/dev-1.x/migration/branches.html) .
+**The default branch is now `main` and the code on the branch has been upgraded to v1.0.0. The old `main` branch (v0.6.3) code now exists on the `0.x` branch.** If you have been using the `main` branch and encounter upgrade issues, please read the [Migration Guide](https://mmocr.readthedocs.io/en/dev-1.x/migration/overview.html) and notes on [Branches](https://mmocr.readthedocs.io/en/dev-1.x/migration/branches.html) .
 
-v1.0.0rc6 was released in 2023-03-07.
+v1.0.0 was released in 2023-04-06. Major updates from 1.0.0rc6 include:
 
-1. Two new models, ABCNet v2 (inference only) and SPTS are added to `projects/` folder.
-2. Announcing `Inferencer`, a unified inference interface in OpenMMLab for everyone's easy access and quick inference with all the pre-trained weights. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/inference.html)
-3. Users can use test-time augmentation for text recognition tasks. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/train_test.html#test-time-augmentation)
-4. Support [batch augmentation](https://openaccess.thecvf.com/content_CVPR_2020/papers/Hoffer_Augment_Your_Batch_Improving_Generalization_Through_Instance_Repetition_CVPR_2020_paper.pdf) through [`BatchAugSampler`](https://github.com/open-mmlab/mmocr/pull/1757), which is a technique used in SPTS.
-5. Dataset Preparer has been refactored to allow more flexible configurations. Besides, users are now able to prepare text recognition datasets in LMDB formats. [Docs](https://mmocr.readthedocs.io/en/dev-1.x/user_guides/data_prepare/dataset_preparer.html#lmdb-format)
-6. Some textspotting datasets have been revised to enhance the correctness and consistency with the common practice.
-7. Potential spurious warnings from `shapely` have been eliminated.
+1. Support for SCUT-CTW1500, SynthText, and MJSynth datasets in Dataset Preparer
+2. Updated FAQ and documentation
+3. Deprecation of file_client_args in favor of backend_args
+4. Added a new MMOCR tutorial notebook
 
+To know more about the updates in MMOCR 1.0, please refer to [What's New in MMOCR 1.x](https://mmocr.readthedocs.io/en/dev-1.x/migration/news.html), or
 Read [Changelog](https://mmocr.readthedocs.io/en/dev-1.x/notes/changelog.html) for more details!
 
 ## Introduction

diff --git a/README_zh-CN.md b/README_zh-CN.md
@@ -65,23 +65,14 @@
 
 **默认分支目前为 `main`，且分支上的代码已经切换到 v1.0.0 版本。旧版 `main` 分支（v0.6.3）的代码现存在 `0.x` 分支上。** 如果您一直在使用 `main` 分支，并遇到升级问题，请阅读 [迁移指南](https://mmocr.readthedocs.io/zh_CN/dev-1.x/migration/overview.html) 和 [分支说明](https://mmocr.readthedocs.io/zh_CN/dev-1.x/migration/branches.html) 。
 
-最新的版本 v1.0.0rc6 于 2023-03-07 发布。
+最新的版本 v1.0.0 于 2023-04-06 发布。其相对于 1.0.0rc6 的主要更新如下：
 
-1. 在 `projects/` 目录中新增了 ABCNet v2 (仅支持推理) 和 SPTS 模型；
+1. Dataset Preparer 中支持了 SCUT-CTW1500, SynthText 和 MJSynth 数据集；
+2. 更新了文档和 FAQ；
+3. 升级文件后端；使用了 `backend_args` 替换 `file_client_args`;
+4. 增加了 MMOCR 教程 notebook。
 
-2. 新增统一推理接口 `Inferencer`，用户可以方便直接地进行各任务的推理。[文档](https://mmocr.readthedocs.io/zh_CN/dev-1.x/user_guides/inference.html)
-
-3. 支持了文本识别任务的测试时数据增强。[文档](https://mmocr.readthedocs.io/zh_CN/dev-1.x/user_guides/train_test.html#id15)
-
-4. 通过 [`BatchAugSampler`](https://github.com/open-mmlab/mmocr/pull/1757) 支持了 [batch augmentation](https://openaccess.thecvf.com/content_CVPR_2020/papers/Hoffer_Augment_Your_Batch_Improving_Generalization_Through_Instance_Repetition_CVPR_2020_paper.pdf) ，这是 SPTS 中使用的一种技巧。
-
-5. 重构了 Dataset Preparer ，用户现在可以更灵活地配置数据集的预处理流程。除此之外，用户现在也可以将文本识别数据集转换为 LMDB 格式。[文档](https://mmocr.readthedocs.io/zh_CN/dev-1.x/user_guides/data_prepare/dataset_preparer.html#lmdb)
-
-6. 修正了一些端到端数据集的标注，保证了数据集的正确性及与常见实践的一致性。
-
-7. 减少了 `shapely` 中可能出现的一些错误警告。
-
-阅读[更新日志](https://mmocr.readthedocs.io/zh_CN/dev-1.x/notes/changelog.html)以获取更多信息。
+如果需要了解 MMOCR 1.0 相对于 0.x 的升级内容，请阅读 [MMOCR 1.x 更新汇总](https://mmocr.readthedocs.io/zh_CN/dev-1.x/migration/news.html)；或者阅读[更新日志](https://mmocr.readthedocs.io/zh_CN/dev-1.x/notes/changelog.html)以获取更多信息。
 
 ## 简介
 

diff --git a/docs/en/get_started/install.md b/docs/en/get_started/install.md
@@ -237,7 +237,8 @@ MMOCR has different version requirements on MMEngine, MMCV and MMDetection at ea
 
 | MMOCR          | MMEngine                    | MMCV                       | MMDetection                 |
 | -------------- | --------------------------- | -------------------------- | --------------------------- |
-| dev-1.x        | 0.7.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
+| dev-1.x        | 0.7.1 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
+| 1.0.0          | 0.7.1 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
 | 1.0.0rc6       | 0.6.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[4-5\] | 0.1.0 \<= mmengine \< 1.0.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[0-3\] | 0.0.0 \<= mmengine \< 0.2.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
diff --git a/docs/en/notes/changelog.md b/docs/en/notes/changelog.md
@@ -2,6 +2,72 @@
 
 ## v1.0.0 (04/06/2023)
 
+We are excited to announce the first official release of MMOCR 1.0, with numerous enhancements, bug fixes, and the introduction of new dataset support!
+
+### 🌟 Highlights
+
+- Support for SCUT-CTW1500, SynthText, and MJSynth datasets
+- Updated FAQ and documentation
+- Deprecation of file_client_args in favor of backend_args
+- Added a new MMOCR tutorial notebook
+
+### 🆕 New Features & Enhancement
+
+- Add SCUT-CTW1500 by @Mountchicken in https://github.com/open-mmlab/mmocr/pull/1677
+- Cherry Pick #1205 by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1774
+- Make lanms-neo optional by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1772
+- SynthText by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1779
+- Deprecate file_client_args and use backend_args instead by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1765
+- MJSynth by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1791
+- Add MMOCR tutorial notebook by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1771
+- decouple batch_size to det_batch_size, rec_batch_size and kie_batch_size in MMOCRInferencer by @hugotong6425 in https://github.com/open-mmlab/mmocr/pull/1801
+- Accepts local-rank in train.py and test.py by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1806
+- update stitch_boxes_into_lines by @cherryjm in https://github.com/open-mmlab/mmocr/pull/1824
+- Add tests for pytorch 2.0 by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1836
+
+### 📝 Docs
+
+- FAQ by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1773
+- Remove LoadImageFromLMDB from docs by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1767
+- Mark projects in docs by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1766
+- add opendatalab download link by @jorie-peng in https://github.com/open-mmlab/mmocr/pull/1753
+- Fix some deadlinks in the docs by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1469
+- Fix quick run by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1775
+- Dataset by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1782
+- Update faq by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1817
+- more social network links by @fengshiwest in https://github.com/open-mmlab/mmocr/pull/1818
+- Update docs after branch switching by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1834
+
+### 🛠️ Bug Fixes:
+
+- Place dicts to .mim by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1781
+- Test svtr_small instead of svtr_tiny by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1786
+- Add pse weight to metafile by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1787
+- Synthtext metafile by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1788
+- Clear up some unused scripts by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1798
+- if dst not exists, when move a single file may raise a file not exists error. by @KevinNuNu in https://github.com/open-mmlab/mmocr/pull/1803
+- CTW1500 by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1814
+- MJSynth & SynthText Dataset Preparer config by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1805
+- Use poly_intersection instead of poly.intersection to avoid sup… by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1811
+- Abinet: fix ValueError: Blur limit must be odd when centered=True. Got: (3, 6) by @hugotong6425 in https://github.com/open-mmlab/mmocr/pull/1821
+- Bug generated during kie inference visualization by @Yangget in https://github.com/open-mmlab/mmocr/pull/1830
+- Revert sync bn in inferencer by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1832
+- Fix mmdet digit version by @gaotongxiao in https://github.com/open-mmlab/mmocr/pull/1840
+
+### 🎉 New Contributors
+
+- @jorie-peng made their first contribution in https://github.com/open-mmlab/mmocr/pull/1753
+- @hugotong6425 made their first contribution in https://github.com/open-mmlab/mmocr/pull/1801
+- @fengshiwest made their first contribution in https://github.com/open-mmlab/mmocr/pull/1818
+- @cherryjm made their first contribution in https://github.com/open-mmlab/mmocr/pull/1824
+- @Yangget made their first contribution in https://github.com/open-mmlab/mmocr/pull/1830
+
+Thank you to all the contributors for making this release possible! We're excited about the new features and enhancements in this version, and we're looking forward to your feedback and continued support. Happy coding! 🚀
+
+**Full Changelog**: https://github.com/open-mmlab/mmocr/compare/v1.0.0rc6...v1.0.0
+
+### Highlights
+
 ## v1.0.0rc6 (03/07/2023)
 
 ### Highlights

diff --git a/docs/zh_cn/get_started/install.md b/docs/zh_cn/get_started/install.md
@@ -236,7 +236,8 @@ docker run --gpus all --shm-size=8g -it -v {实际数据目录}:/mmocr/data mmoc
 
 | MMOCR          | MMEngine                    | MMCV                       | MMDetection                 |
 | -------------- | --------------------------- | -------------------------- | --------------------------- |
-| dev-1.x        | 0.7.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
+| dev-1.x        | 0.7.1 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
+| 1.0.0          | 0.7.1 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
 | 1.0.0rc6       | 0.6.0 \<= mmengine \< 1.0.0 | 2.0.0rc4 \<= mmcv \< 2.1.0 | 3.0.0rc5 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[4-5\] | 0.1.0 \<= mmengine \< 1.0.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
 | 1.0.0rc\[0-3\] | 0.0.0 \<= mmengine \< 0.2.0 | 2.0.0rc1 \<= mmcv \< 2.1.0 | 3.0.0rc0 \<= mmdet \< 3.1.0 |
diff --git a/mmocr/__init__.py b/mmocr/__init__.py
@@ -16,7 +16,7 @@
 mmcv_maximum_version = '2.1.0'
 mmcv_version = digit_version(mmcv.__version__)
 if mmengine is not None:
-    mmengine_minimum_version = '0.6.0'
+    mmengine_minimum_version = '0.7.1'
     mmengine_maximum_version = '1.0.0'
     mmengine_version = digit_version(mmengine.__version__)
 

diff --git a/mmocr/version.py b/mmocr/version.py
@@ -1,4 +1,4 @@
 # Copyright (c) Open-MMLab. All rights reserved.
 
-__version__ = '1.0.0rc6'
+__version__ = '1.0.0'
 short_version = __version__